The Internet and World Wide Web (hereinafter the “Net”) provide users with convenient access to information. The exponential growth of the Net has generated vast quantities of data that is available to users of the Net at the click of a mouse. However, an incidental but important consequence of the widespread use of the Net is the information created by users of the Net (hereinafter “user-specific usage data”). Users of the Net generate data by connecting to various locations (computers, applications, and files) comprising and connected to the Net. For example, user-specific usage data may take the form of requests that are transmitted by a user's web browser, on behalf of the user. User-specific usage data is also generated as the user interacts with web sites and applications linked to the Net. User-specific usage data reflects a user's interests, and therefore constitutes a potentially valuable source of market and demographic information.
Useful knowledge can be interpreted from the user-specific usage data to support and provide direction for e-business decisions. For example, the data can be mined for user profiles, subsequently used by businesses to customize their on-line advertisements of services and products to targeted segments of consumers. Other uses include but are not limited to customizing a user's interaction with a web site based on the user's profile. To illustrate, assume user G visits the Acme Book company web site, and the profile of user G indicates that G is an avid golfer, then Acme Book company may choose to send G a customized web page to include a list of books on the subject of golf. Still other uses of user profiles include but are not limited to sending political campaign advertising, public service announcements, or other solicitations to target segments of Net users.
A business can make strategic and tactical decisions based on the user-specific usage data derived from data generated by a Net user's interaction. For example, a Net user's pattern of interactions with different applications, files, and computers on the Net may reveal the user's preference for certain Net functions over competitor's Net functions. If a great many users exhibit similar preferences, and it is determined that the users are a target customer-base for a business, then the business may take appropriate action to better meet the needs of the target customer-base. For example, the business may modify its offerings of services and products or otherwise improve its Net site to enhance a user's interaction with the site.
As another example, a Net user's patterns of Net interactions may be helpful in attempting to predict what content the user may be interested in viewing and thus, the relevant Net pages of such content may be proactively made available to the user. To illustrate, suppose a user's Net interaction history includes visits to various Net sites featuring exclusive real estate, yachts, and private jets. Using inductive reasoning, one might hazard a guess that this particular user might be interested in receiving Net information featuring articles on the lives of the rich and famous.
Another illustration of useful knowledge that can be interpreted from the data generated by a Net user's Net interactions is the identification of a network of sites that represent complementary products and services. For example, the Net interaction habits of a customer segment that favors fine wine may be used to identify a group of companies of complementary products and services, which can collaborate and coordinate their offerings to that segment of wine connoisseurs.
The user-specific usage data gathered from the Net is also valuable to businesses that do not have an on-line presence. Any business may profit by making business decisions based on information on market trends and the demography of customer segments derived from the Net interaction generated data.
While user-specific usage data is potentially valuable, the challenge is knowing how to collect the user-specific usage data, what data to collect and, once the data is collected, how to organize, manipulate and mine the collected data to produce useful knowledge. Thus, there is a need for a system or mechanism that delivers on demand, actionable knowledge of Net user's Net interactions.